• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.260-269
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• 2000

The fuzzy and state-feedback control systems have been applied in various areas from non-linear to linear systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. though apply back-propagation algorithm to the system, the convergence time a much. Besides, the state-feedback system is most widely used in industry due to its simple control structure and easily able to design the controller. but it is weak in complex system of higher degree and non-linear. In this paper presents the design of a fuzzy switching mode, it these two controllers work at different operation conditions, the advantages of both controller can be retained and the disadvantages can be removed. Between the Fuzzy and the State-feedback controlles, the good outputs are selected by the switching mode. Moreover it is powerful in complex system of higher degree and non-linear. In these sense compared with the state-feedback controller, the performance of the proposed controller was improvedin the section of linearization.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.1
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• pp.16-23
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• 2004

Permanent magnet-excited transverse flux linear motor(TFLM) is known to have more excellent ratio of force to weight than any other linear motors. But, thrust generated by phase current is non-linear with regard to current and relative position like switched reluctance motor. This makes current and speed controller design difficult. This paper presents a method on minimization of thrust ripple of permanent magnet-excited transverse flux linear motor. Using genetic algorithm(GA), optimal current waveform can be found under the constraint conditions such as current limit, minimum of ohmic loss and limited rate of change of current etc. The effectiveness is verified through computer simulation and experimental test results.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.252-258
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• 2007

In this paper, a face recognition algorithm system using Principal Component Analysis (PCA) is proposed. The algorithm recognized a person by comparing characteristics (features) of the face to those of known individuals of Intelligent Control Laboratory (ICONL) face database. Simulations are carried out to investigate the algorithm recognition performance, which classified the face as a face or non-face and then classified it as known or unknown one. Particularly, a Principal Components of Linear Discriminant Analysis (PCA + LDA) face recognition algorithm is also proposed in order to confirm the recognition performances and the adaptability of a proposed PCA for a certain specific system.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.11-16
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• 2013

This paper presents a unified control algorithm of independent braking and steering for collision avoidance. The desired motion of the vehicle in the yaw plane is determined using the probabilistic risk assessment method based on target state estimation. For the purpose of coordinating the independent braking and steering, a non-linear vehicle model has been developed, which describes the vehicle dynamics in the yaw plane in both linear and extended non-linear ranges of handling. A control allocation algorithm determines the control inputs that minimize the difference between the desired and actual vehicle motions, while satisfying all actuator constraints. The performance of the proposed control algorithm has been investigated via computer simulations conducted using the vehicle dynamics software CARSIM and Matlab/Simulink.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.933-946
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• 2021

In the non-orthogonal multiple access (NOMA) system, multiple user signals on the single carrier are superimposed in a non-orthogonal manner, which results in the interference between non-orthogonal users and noise interference in the channel. To solve this problem, an improved algorithm combining regularized zero-forcing (RZF) precoding with minimum mean square error-serial interference cancellation (MMSE-SIC) detection is proposed. The algorithm uses RZF precoding combined with successive over-relaxation (SOR) method at the base station to preprocess the source signal, which can balance the effects of non-orthogonal inter-user interference and noise interference, and generate a precoded signal suitable for transmission in the channel. At the receiver, the MMSE-SIC detection algorithm is used to further eliminate the interference in the signal for the received superimposed signal, and reduce the calculation complexity through the QR decomposition of the matrix. The simulation results show that the proposed joint detection algorithm has good applicability to eliminate the interference of non-orthogonal users, and it has low complexity and fast convergence speed. Compared with other traditional method, the improved method has lower error rate under different signal-to-interference and noise ratio (SINR).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.180-186
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• 2009

Due to the large capacity and low cost, electrolytic capacitors with of energy storage and voltage regulation are used for almost all types of non-linear load as the DC/DC converter. Electrolytic capacitor, which is the most of the time affected by the aging effect, plays very important role for the power converter system quality and reliability. Therefore, this paper proposes a new method to detect the changes the capacitance value of an electrolytic capacitor in order to analyze the internal characteristic and worn-out state of an electrolytic capacitor. Simulation results by frequency analysis show the validity of the proposed capacitance estimation algorithm.

• Journal of Ocean Engineering and Technology
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• v.18 no.2
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• pp.77-82
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• 2004

The purpose of this study is to develop a nesting algorithm, using a genetic algorithm to optimize nesting order, and modified No Fit Polygon(NFP) methodology to place parts with the order generated from the previous genetic algorithm. Various genetic algorithm techniques, which have thus far been applied to the Travelling Salesman Problem, were tested. The partially mapped crossover method, the inversion method for mutation, the elitist strategy, and the linear scaling method of fitness value were selected to optimize the nesting order. A modified NFP methodology, with improved searching capability for non-convex polygon, was applied repeatedly to the placement of parts according to the order generated from previous genetic algorithm. Modified NFP, combined with the genetic algorithms that have been proven in TSP, were applied to the nesting problem. For two example cases, the combined nesting algorithm, proposed in this study, shows better results than that from previous studies.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.215-218
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• 1997

A dynamic back-propagation neural network is addressed for adaptive neural control system to approximate non-linear control system rather than static networks. It has the capability to represent the approximation of nonlinear system without mathematical analysis and to carry out the on-line learning algorithm for real time application. The simulated results show fast tracking capability and adaptive response by using dynamic back-propagation neurons.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.293-295
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• 1993

In this paper, Neural-Network Identifier that has time-delay element, error limit and small weighting factor is proposed. A proposed identifier has good performance to identify non-linear system with noise. To test the effectiveness of the algorithm presented above, the simulation for output tracking of non-linear system is implemented.

• The Journal of Information Technology and Database
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• v.7 no.2
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• pp.47-59
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• 2000

In this paper, we analyze the applicability of a general optimization algorithm to a database optimization problem. The index selection problem Is the problem to choose a set of indexes for a database in a way that the cost to process queries in the given workload is minimized subject to a given storage space restriction for storing indexes. The problem is well known in database research fields, and many optimization and/or heuristic algorithms have been proposed. Our work differs from previous research in that we formalize the problem in the form of non-linear Integer Programming model, and investigate the feasibility and applicability of a general purpose optimization algorithm, called OPBDP, through experiments. We implemented algorithms to generate workload data sets and problem instances for the experiment. The OPBDP algorithm, which is a non-linear 0-1 Integer Programming problem solver based on Davis-Putnam method, worked generally well for our problem formulation. The experiment result showed various performance characteristics depending on the types of decision variables, variable navigation methods and ocher algorithm parameters, and indicates the need of further study on the exploitation of the general purpose optimization techniques for the optimization problems in database area.